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• Temporary continuous observation task using non-customized constellation is studied. • A hybrid method for multi-satellite scheduling and task planning is proposed. • A joint simulation software system is developed via STK and Python. • The proposed technique has higher efficiency and target adaptability. This paper put forward a method to address the problem, of how to select multiple satellites from a given heterogeneous constellation and plan their tasks to implement a temporary mission for ground or aerial targets successive observation, while hardly affecting the constellation's original mission as much as possible. First, considering the observation geometric constraints of the satellite on the target, an observability analysis model for effective observation of the satellite on the target is established to characterize the observable spatio-temporal scope. Considering the time-length requirement of sustained observation on the target, a multi-satellite-to-target sustained observation model is constructed for the scheduling of satellites. Second, to address the problem of selecting task satellites in a given heterogeneous constellation, a mathematical model for task planning is established to maximize observation benefits and minimize task burdens. Third, a hybrid method of multi-satellite scheduling and task planning is designed with fault tolerance, based on dynamic programming and an improved contract network protocol algorithm. Next, a joint simulation software system is established through the secondary development of STK and Python, which includes satellite-target observability analysis, task satellite selection, task allocation and planning, and full process visible demonstration functions. Finally, simulation cases verified the effectiveness and superiority of the proposed technique. [ABSTRACT FROM AUTHOR]

An emerging threat within blockchain systems is the malicious tactic known as eclipse attacks, wherein attackers aim to deceive and gain control over targeted nodes. Despite the increasing popularity of blockchain technology, effective defence mechanisms against eclipse attacks have been lacking. A novel and dynamic defence model designed explicitly for Proof-of-Work (PoW) consensus blockchain systems is proposed to address this critical issue. The model relies on a node-to-node evaluation mechanism to ensure robust protection. By leveraging mutual evaluations conducted between clients and incorporating the renowned Kademlia algorithm, a ranking value is assigned to each node within the defence model. These rankings empower nodes to prudently select trustworthy peers as neighbours based on a threshold comparison, effectively mitigating the risk posed by malicious nodes. Notably, the proposed approach significantly enhances the security of blockchain systems without necessitating modifications to existing protocols or network structures. The effectiveness of the proposed defence model in countering eclipse attacks is extensively validated through a series of experiments. Furthermore, the approach surpasses previous defence strategies, offering a higher probability of successful defence while maintaining minimal overhead. With its straightforward implementation and operational efficiency, the dynamic defence model is an ideal solution for real-world deployment scenarios. This research presents a compelling and robust defence model against eclipse attacks in PoW blockchain systems, addressing the existing gap in defence mechanisms. Furthermore, this advancement paves the way for the wider adoption of blockchain applications across various domains by providing enhanced security, reliability, and trustworthiness. [ABSTRACT FROM AUTHOR]

Due to the boom of Internet of Things (IoT) in recent years, various IoT devices are connected to the Internet and communicate with each other through network protocols such as the Constrained Application Protocol (CoAP). These protocols are typically defined and described in specification documents, such as Request for Comments (RFC), which are written in natural or semi-formal languages. Since developers largely follow the specification documents when implementing web protocols, they have become the de facto protocol specifications. Therefore, it must be ensured that the descriptions in them are consistent to avoid technological issues, incompatibility, security risks, or even legal concerns. In this work, we propose Neural RFC Knowledge Graph (NRFCKG), a neural network-generated knowledge graph based contradictions detection tool for IoT protocol specification documents. Our approach can automatically parse the specification documents and construct knowledge graphs from them through entity extraction, relation extraction, and rule extraction with large language models. It then conducts an intra-entity and inter-entity contradiction detection over the generated knowledge graph. We implement NRFCKG and apply it to the most extensively used messaging protocols in IoT, including the main RFC (RFC7252) of CoAP, the specification document of MQTT, and the specification document of AMQP. Our evaluation shows that NRFCKG generalizes well to other specification documents and it manages to detect contradictions from these IoT protocol specification documents. [ABSTRACT FROM AUTHOR]

This paper investigates an observer-based state estimation issue for discrete-time semi-Markovian jump neural networks with Round-Robin protocol and cyber attacks. In order to avoid the network congestion and save the communication resources, the Round-Robin protocol is used to schedule the data transmissions over the networks. Specifically, the cyber attacks are modeled as a set of random variables satisfying the Bernoulli distribution. On the basis of the Lyapunov functional and the discrete Wirtinger-based inequality technique, some sufficient conditions are established to guarantee the dissipativity performance and mean square exponential stability of the argument system. In order to compute the estimator gain parameters, a linear matrix inequality approach is utilized. Finally, two illustrative examples are provided to demonstrate the effectiveness of the proposed state estimation algorithm. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of fixed-time consensus tracking for a class of nonlinear multi-agent systems subject to unknown disturbances. Firstly, a modified fixed-time disturbance observer is devised to estimate the unknown mismatched disturbance. Secondly, a distributed fixed-time neural network control protocol is designed, in which neural network is employed to approximate the uncertain nonlinear function. Simultaneously, the technique of command filter is applied to fixed-time control, which circumvents the "explosion of complexity" problem. Under the proposed control strategy, all agents are enable to track the desired trajectory in fixed-time, and the consensus tracking error and disturbance estimation error converge to an arbitrarily small neighborhood of the origin, meanwhile, all signals in the closed-loop system remain bounded. Finally, a simulation example is provided to validate the effectiveness of the presented design method. [ABSTRACT FROM AUTHOR]

Evaluate the differences between clinical visual acuity (VA) as recorded in medical records and electronic Early Treatment Diabetic Retinopathy Study (eETDRS) protocol VA measurements and factors affecting the size of the differences. Retrospective chart review. Study and fellow eyes of participants enrolled in DRCR Retina Network Protocols AC and AE (diabetic macular edema), and W (nonproliferative diabetic retinopathy) with clinical VA recorded within 3 months before the protocol visit. Differences and their association with patient and ocular factors were evaluated using linear mixed models with random effects for correlations within sites and participants. Difference between VA letter scores measured by eETDRS during a study visit versus measured by Snellen during a regular clinical visit (Snellen fraction converted to eETDRS). Data from 1016 eyes (511 participants) across 74 sites were analyzed. The mean VA measurements were 68.6 letters (Snellen equivalent 20/50) at the clinical visit and 76.3 letters (Snellen equivalent 20/32) at the protocol visit, with a mean (standard deviation [SD]) of 26 (21) days between visits. Mean (SD) protocol VA was better than clinical VA by 7.6 (9.6) letters overall, 10.7 (12.6) letters in eyes with clinical VA ≤ 20/50 (n = 376), and 5.8 (6.6) letters in eyes with clinical VA ≥ 20/40 (n = 640). On average, the difference between clinical and protocol VA was 1.3 letters smaller for every 1-line (5 letters) increase in clinical VA (P < 0.001). Mean (SD) differences by clinical correction of refractive error were 3.9 (9.0) letters with refraction, 6.9 (9.2) letters with glasses/contact lenses, 7.9 (11.5) letters with pinhole, and 9.8 (9.3) letters without correction (P = 0.06). On average, clinical Snellen VA is 1 to 2 lines worse than eETDRS protocol refraction and VA testing, which may partly explain why clinical practice does not always replicate clinical trial results. Eyes with lower clinical measurements and eyes tested without clinical refraction tended to have larger differences. Considering the potential discrepancies between clinical and protocol VA measurements, refracting eyes in the clinic may benefit patients when determining treatment plans and study referrals based on vision. Proprietary or commercial disclosure may be found after the references. [ABSTRACT FROM AUTHOR]

When controlling cyber–physical systems via consensus algorithms, the robustness issue is of paramount importance because of model mismatching and/or disturbances that generally modify the Laplacian flow dynamics associated to the overall network, compromising the possibility to achieve any expected, orchestrated emergent behavior. To face this issue, the Variable Structure Control (VSC) approach has recently been shown to be an effective tool in designing control protocols over networks, providing robustness and often yielding finite-time convergence. Moreover, VSC further enables the decoupling of simultaneous control objectives where reaching a consensus state is only part of a more complex task, for instance as it happens in distributed optimization. Thus motivated, this paper overviews, from a tutorial perspective, some selected recent advances in the application of VSC with Sliding Modes to design robust consensus controllers in both the leader-less and the leader-following settings. Efforts are also made to unify the notation and to discuss the theoretical foundations of the nonsmooth analysis tools at the basis of their design for a wide readership unfamiliar with these problems and formal tools. To this aim, examples supporting the treatment, and numerical simulations, are given and discussed in detail. Finally, hints for future investigations along with some current open problems are provided. [ABSTRACT FROM AUTHOR]

In today's world of wireless communication, the prime point of concentration lies on data security. This depends mainly on proper authentication of users who are intended to connect to the network. with modern day technology, the credentials (password), which the legitimate user send to the access points for his/her authorization, can be sniffed and used to enter the system, compromising the system security. WPA2/PSK (Wireless Protected Access/Pre-Shared Key) has a vulnerability which allows an attacker to perform Man-in-the-middle attack by capturing the handshake sent by the legitimate user for authentication. The captured handshake can be used to recover the password using dictionary attack or can be brute forced. To overcome the short comings of the current system, the proposed method uses Frequency Hopping Technique to secure the MIC(Message Integrity Code) before transmitting it. This method reduces the possibility of brute forcing the password, even if the handshake is captured. [ABSTRACT FROM AUTHOR]

This work presents a dynamic posture tracking control strategy for wheel-legged systems on uneven surfaces. Based on the kinematic model of a wheel-legged robotic system, the expected positions for the end-effectors of wheel-legs are calculated according to posture references and sensor feedback. The position control problem for a general wheel-leg is investigated for the active mechanism to imitate a passive suspension and respond to the external contact forces. The position tracking accuracy of the wheel-leg is sacrificed to enhance the compliance performance under rough terrain. Because of the unique contact state with the uneven ground for each wheel-leg, the position responses are different. As a result, the forces from the wheel-legs to the fuselage are inconsistent, which leads to the risk of posture oscillations. Equipping the wheel-legs with an undirected communication network, a consensus scheme for the robotic system is developed with proven global asymptotic stability to improve the posture tracking property. A novel robotic system is established with Stewart-structured wheel-legs, which are connected by a user datagram protocol network. Comparative experimental results are carried out on the physical prototype to validate the effectiveness of the proposed approach. • An improved kinematic model avoiding geomagnetism disturbances is established for general wheel-legged robotic systems. Considering the contact forces, an active suspension controller is proposed for the single wheel-leg to track the desired position with expected compliance behaviors. • Based on an undirected communication topology, a consensus strategy is carried out for multiple ASCs. The CASC fulfills the coordination requirements and active suspension response demands with proved convergency property. • The proposed posture control scheme is applied to a wheel-legged physical prototype. The comparative experimental results between the proposed CASC and our previous studies are presented, which highlights the CASC in posture tracking accuracy and wheel-leg coordination performances. [ABSTRACT FROM AUTHOR]

Logistic regression is a well-known method for classification and is being widely used in our daily life. To obtain a logistic regression model with sufficient accuracy, collecting a large number of data samples from multiple sources is necessary. However, in nowadays a concern about the leakage of private information contained in data samples becomes increasingly prominent, and thus privacy-preserving logistic regression that enables training logistic regression models without privacy leakage has received great attention from the community. Mohassel and Zhang at IEEE S&P'17 presented a significant protocol for privacy-preserving logistic regression in two-server setting, where two non-colluding servers collaboratively train logistic regression models in an offline–online manner. In this work, we propose a new two-server-based protocol for privacy-preserving logistic regression with an efficient approach to activation function evaluation, which incurs much less computational overhead than Mohassel–Zhang protocol while requiring the same number of online rounds. We also present a round-efficient protocol for generating correlated randomness that will be used subsequently in our activation function evaluation. We implement our protocol in C++ and the experimental results validate its efficiency. [ABSTRACT FROM AUTHOR]

The significance of cognitive radios in satisfying the growing demand for bandwidth in wireless networks is anticipated to be significant. An innovative method for cognitive network beamforming and interference control based on machine learning and an intelligent network protocol is suggested in this study. A Reinforcement Nash Equilibrium Game Theory (RNEGT) model is used to control network interference, and the Spatiotemporal Non-Orthogonal Multiple Access (ST-NOMA) technique is used for beamforming inside the network. Throughput, spectrum efficiency, stability, Mean Square Error (MSE), and Signal-to-Interference and Noise Ratio (SINR) are some of the metrics used in experimental study. Examined approach can optimize received SINR at destinations while maintaining interference + noise power below a certain threshold by employing the suggested relay selection and a cooperative beamforming (CBF) mechanism in each cluster. [ABSTRACT FROM AUTHOR]

Exercise induced performance fatigue has been shown to impair many aspects of fine motor function in the distal upper limb. However, most fatiguing protocols do not reflect the conditions experienced with computer use. The purpose of this study was to determine how a prolonged, low-force mouse clicking fatigue protocol impacts performance fatigue of the distal upper limb for gamers and non-gamers. Participants completed a total of 1 h of mouse clicking at 5 clicks per second. Muscle fatigue and performance were intermittently assessed. RMS amplitude increased for the forearm flexors throughout the fatigue protocol. Accuracy decreased following the first bout of clicking and returned to baseline values after 40-min. EDC and ECU displayed the greatest muscle activity while aiming, producing 11.4% and 12.9% of MVC, respectively. These findings indicate that mouse clicking may not result in performance fatigue, however, high levels of extensor activity may explain common injuries among gamers. [ABSTRACT FROM AUTHOR]

Traditional partial synchronous Byzantine fault tolerant (BFT) protocols are confronted with new challenges when applied to large-scale networks like IoT systems, which bring about rigorous demand for the liveness and consensus efficiency of BFT protocols in asynchronous network environments. HoneyBadgerBFT is the first practical asynchronous BFT protocol, which employs a reliable broadcast protocol (RBC) to broadcast transactions and an asynchronous binary agreement protocol (ABA) to determine whether transactions should be committed. DumboBFT is a follow-up proposal that requires fewer instances of ABA and achieves higher throughput than HoneyBadgerBFT, but it does not optimize the communication overhead of HoneyBadgerBFT. In this paper, we propose TortoiseBFT, a high-performance asynchronous BFT protocol with three stages. We can significantly reduce communication overhead by determining the order of transactions first and requesting missing transactions after. Our two-phase transaction recovery mechanism enables nodes to recover missing transactions by seeking help from 2 f + 1 nodes. To improve the overall throughput of the system, we lower the verification overhead of threshold signatures in HoneyBadgerBFT, DumboBFT, and DispersedLedger from O n 3 to O n 2 . We develop a node reputation model that selects producers with stable network conditions, which helps to reduce the number of random lotteries. Experimental results show that TortoiseBFT improves system throughput, reduces transaction delays, and minimizes communication overhead compared to HoneyBadgerBFT, DumboBFT, and DispersedLedger. [ABSTRACT FROM AUTHOR]

This paper considers the reliable state estimation issue for discrete-time neural networks with the try-once-discard (TOD) scheduling protocol and mixed compensation strategy. For the phenomenon of medium access constraint, the measurement transmitted from sensors to the estimator is subjected to the TOD scheduling protocol. The mixed compensation is proposed to flexibly compensate those missing measurements caused by the TOD protocol. By using a novel polytopic uncertain model, a reliable state estimator is designed, where the gain matrix is determined by two vertex matrices. Then sufficient conditions are established, which ensure the error system meets the stochastic stability and the l 2 - l ∞ performance. Finally, an illustrative example shows the validity of the proposed reliable state estimator. [ABSTRACT FROM AUTHOR]

During this last past decade, the Internet of Things (IoT) has gained much attention because it encompass intelligent devices such as smart sensors and actuators, which enable a wide range of applications that improve our daily life (e.g. smart agriculture). However, due to the presence of an important number of heterogeneous and resources constrained devices (in terms of memory, CPU and bandwidth) communicating over error-prone and lossy radio channels and often deployed in hostile environments (e.g. war zone), IoT networks are experiencing various network performance problems (e.g. excessive energy consumption resulting from network device failure). In this context, an efficient management of IoT networks is needed in order to ensure good network performances. This has fueled the development of different protocols and frameworks for management of IoT networks. In this paper we present a comprehensive study of representative works on IoT network management. The paper analyzes existing solutions for IoT low power networks management and presents a taxonomy of those solutions. Moreover, this paper also compares existing research proposals on management of IoT low power networks based on different requirements. At the end, this survey identifies remaining challenges for an efficient mangement of IoT low power networks. [ABSTRACT FROM AUTHOR]

Colombia government wants to implement electronic voting. However, the existing electronic voting protocols only include some of the required security features and Colombia needs a protocol with all these features to ensure fraud-free elections. In this paper, we present the design of SIVP (Secure Internet Voting Protocol), a new voting protocol for electoral processes, based on blind signatures and public key cryptography. This protocol has six phases and provides: eligibility, democracy, privacy, verifiability, accuracy, fairness, robustness, receipt-freeness and coercion-resistant. Also, we compare the number of cryptographic operations per phase of SIVP with other four protocols and conclude that the computational load of our protocol is not excessively high despite including more security features. [ABSTRACT FROM AUTHOR]

Although the area of underwater acoustic networking is getting mature and critical for a wide variety of commercial applications, the lack of secure underwater communication standards presents a major impediment for adopting these networking technologies within NATO operations. The NATO Research Task Group IST-174 "Secure Underwater Communications for Heterogeneous Network-enabled Operations" aims to study and to demonstrate secure underwater communications in a holistic approach. In particular, this group's ambition is to define waveforms, network protocols and architectures that will enable underwater connectivity in a secure and interoperable way. To that effect, this paper presents various security concepts and communication systems currently under development that could be included in those standardisation efforts. [ABSTRACT FROM AUTHOR]

• The Network Canvas suite consists of three applications: Architect ; Interviewer ; Server. • These applications simplify the collection of complex social network data. • Our work prioritizes flexibility, intuitive design, integrated workflow, and collaboration. Self-reported social network analysis studies are often complex and burdensome, both during the interview process itself, and when conducting data management following the interview. Through funding obtained from the National Institute on Drug Abuse (NIDA/NIH), our team developed the Network Canvas suite of software – a set of complementary tools that are designed to simplify the collection and storage of complex social network data, with an emphasis on usability and accessibility across platforms and devices, and guided by the practical needs of researchers. The suite consists of three applications: Architect: an application for researchers to design and export interview protocols; Interviewer: a touch-optimized application for loading and administering interview protocols to study participants; and Server: an application for researchers to manage the interview deployment process and export their data for analysis. Together, they enable researchers with minimal technological expertise to access a complete research workflow, by building their own network interview protocols, deploying these protocols widely within a variety of contexts, and immediately attaining the resulting data from a secure central location. In this paper, we outline the critical decisions taken in developing this suite of tools for the network research community. We also describe the work which guides our decision-making, including prior experiences and key discovery events. We focus on key design choices, taken for theoretical, philosophical, and pragmatic reasons, and outline their strengths and limitations. [ABSTRACT FROM AUTHOR]

An increase in digitization is giving rise to cybercrimes. The existing network protocols are insufficient for collecting the required digital evidence of cybercrime, which eventually makes the process of forensic investigation difficult. In the current scenario of network forensics, the investigator with current capabilities can reach only up to the ISP. This is not primary evidence. Currently, available tools work only at the network layer. In this work, we propose a protocol that ensures tracking up to the true source by collecting beforehand forensically sound evidence. The proposed protocol can collect target data from the device in the form of a device fingerprint with the help of an agent process. The proposed methodology will help in proving non-repudiation, which is a well-known challenge in forensic cases. The fingerprint evidence generated by the proposed method has the capability of not getting obsolete even if the criminal tries to destroy evidence. The fingerprinting technique deployed uses a hash tree and generates evidence in such a way that this fingerprint can act as legal evidence. The security validation of the proposed system is done using the BAN logic. Formal verification is performed using the AVISPA tool. The system has been implemented as a prototype and hosted on AWS. [ABSTRACT FROM AUTHOR]

Internet applications such as video gaming virtual/ augmented reality necessitate efficient fifth-generation (5G) millimeter-wave (mmWave) cellular networks. The Transmission Control Protocol (TCP) is an essential protocol for network connectivity. However, TCP faces challenges in efficiently utilizing the available bandwidth of 5G mmWave cellular networks while maintaining low latency, mainly due to constraints like Non-Line of Sight (NLoS) conditions. This paper introduces Round-Trip-Time Variations-TCP (RTTV-TCP), enhancing TCP performance in 5G mmWave cellular networks. Simulation scenarios for a 5G mmWave cellular network have been conducted to evaluate RTTV-TCP's performance, comparing it to legacy TCP variants such as NewReno, HighSpeed, CUBIC, Bottleneck Bandwidth and Round-trip propagation time (BBR), FB-TCP (Fuzzy Based-TCP). The results demonstrate that RTTV-TCP achieves higher average throughput than these TCP variants while maintaining the same level of delay in 5G mmWave cellular networks. RTTV-TCP outperforms NewReno and CUBIC by a very significant margin, demonstrating a 208% improvement compared to HighSpeed and a 6% increase compared to BBR protocol in the worst Packet Error Rate (PER) scenario and when the buffer size matches the Bandwidth Delay Product (BDP). [ABSTRACT FROM AUTHOR]

The accurate identification of internet traffic is crucial for network management. However, the use of encryption techniques and constant changes in network protocols make it difficult to extract useful features for traffic classification. Additionally, there may be limited data availability and a lack of diversity within the dataset, which poses further challenges. To address these issues, our research proposes a novel solution that uses an innovative data augmentation technique. This approach leverages the capabilities of LSTM networks to create synthetic data points that closely resemble real traffic data. By doing so, we can significantly enrich the dataset used for training and improve classification efficiency. We conducted thorough experiments to validate our approach and found that combining LSTM-generated data with actual traffic data leads to notable improvements in classification efficiency. We demonstrated the effectiveness of our methodology using academic and commercial datasets. Our classifier, trained on the generated data, showed a performance boost of 6%. Moreover, when classifying with only half of the time, thus utilizing half of the signal, our approach achieved a notable 4% improvement compared to the original classifier. The inclusion of augmented samples within the training set led to a noticeable improvement in both accuracy and F1-score. These findings compellingly demonstrate our data augmentation strategy's practical utility and efficiency in earlier prediction with improved performance for encrypted traffic classification systems. • Enhanced Traffic Analysis via LSTM Augmentation. • Efficiency Boost: Earlier Traffic Classification. • Improved Classifier Performance with Generated Data. • Diverse Data Synthesis for Improved Classification. [ABSTRACT FROM AUTHOR]

• Development of the Depth-Based Stable Election Routing Protocol, which is specifically designed for underwater environments, by combining the probabilistic CH election approach and stable election protocol to improve the stability and efficiency of the proposed routing protocol. • Consideration of energy efficiency as a priority, in addition to tackling the difficulty of energy imbalance in varied IoUT scenarios, by recognizing efficient energy utilization as a major issue in IoUT. • Use fitness functions adapted to underwater nodes with varying energy levels and depths. • The suggested depth-based SEP-IoUT protocol was compared to conventional SEP and SEP-IoUT protocols. Furthermore, higher performance in terms of network lifetime, stability period, and energy consumption reduction must be demonstrated. Internet of underwater things (IoUT) is a technology enabling underwater sensor nodes to communicate with the IoT networks to support various applications. Efficient energy utilization and network lifetime are the two main critical issues related to the IoUT. Both performance factors are related to how efficiently the routing protocol is tailored especially for heterogeneous IoUT. In this context, efficient routing protocols that consider underwater nodes (UNs) energy heterogeneity can adjust the energy imbalance, especially in heterogeneous IoUT scenarios. In IoUT, both the UN's energies and their depths can greatly affect the energy efficiency and clustering-based routing protocol. This paper provided an energy and depth-based stable election routing protocol (SEP) to suit the requirements of underwater communications. The objective of the depth-based SEP protocol is to enhance energy-efficient routing while considering the varying energy levels of UNs in IoUT. The proposed protocol depends on the depth-based cluster head (CH) election approach by defining distinct functions tailored for UNs with different energy levels and depths, in addition to the distance between the selected CH and the surface base station. Experimental results indicate that depth-based SEP-IoUT protocol outperforms network lifetime more than conventional SEP and SEP-IoUT. It gives an average stability period of 19.6 % in addition to reducing energy consumption by 39 % and 15.7 % when compared to SEP and SEP-IoUT respectively. [ABSTRACT FROM AUTHOR]

• 31 years of Birch pollen records in the northwestern Iberian Peninsula. • Precipitation in early spring delays the onset of the pollen period. • Pollen intensity in the last decades is increasing. • Temperature during the pollen period affects each locality differently. • Pre-summer temperature increases pollen intensity at all studies locations We studied the relationship between the occurrence of airborne pollen of Betula spp. and climate, during the main pollination season, as well as before the pollen season and in the preceding year. Our aim was to understand how environmental conditions could influence the main pollen season and the intensity of airborne pollen presence at the meridional boundary of the Betula forest distribution in Europe. For this purpose, pollen monitoring was conducted using Lanzoni VPPS 2000 volumetric trap and weather data from the nearest meteorological station. The study area was located in the northwest of the Iberian Peninsula, specifically in three areas with diverse mesoclimate: Vigo (Atlantic), Ourense (Mediterranean) and Lugo (Cantabrian), which had a distinct oceanic influence. Aerobiological analysis was conducted based on the Spanish aerobiology network protocol. Data on precipitation, maximum, minimum and mean temperature were selected for three time windows: 1st the main pollen season period, 2nd from 5 to 90 days before the onset of pollen presence, with a cumulative five-day interval, and 3rd the average monthly climate of the previous year. Precipitation delays the onset of the main pollination season as well as the end of the season, increasing pollen counts in the post-peak interval at all three sites. Temperature during the pollen season affects duration and pollen integral differently among sites. The pollen integral shows an increasing trend over the last decade's at all three areas. The rise trend detected in the minimum temperature of the previous summer explains these increases in the three sites. In conclusion, the effect of climate prior to and during the main pollen season have varied effects on date-related data across mesoclimates, while temperature during bud floral primordia development can be considered as a timeframe for predicting pollen intensity in the following year through the entire area. [ABSTRACT FROM AUTHOR]

Developing a highly efficient multi-node media access control protocol tailored for ultraviolet (UV) networks poses a significant challenge. While our team's UV random-access collaborative networking protocol, utilizing time-division multiple access (UVCN-TDMA), has been instrumental, its scalability is hindered by the number of network nodes. To address this limitation and facilitate large-scale UV node networking, this study advances the UVCN protocol by introducing an enhanced collaborative networking protocol known as the enhanced collaborative clustering mechanism (eCOCM). This study examined the impact of network topology, various data services, and the number of cluster nodes on network performance within the proposed eCOCM framework. Additionally, a comparative analysis between the eCOCM protocol and conventional clustering systems was conducted. The findings demonstrate notable enhancements across key performance metrics including throughput, packet loss rate, delay, and channel utilization. Finally, functional experiments were conducted under two distinct network scenarios to validate the efficacy of the proposed protocol. This study addresses the immediate challenges in UV multi-node networking and offers pragmatic insights to steer its development forward. • This study proposes an enhanced collaborative networking protocol based on a clustering mechanism (eCOCM) to cope with large-scale Ultraviolet (UV) node networking. • The effects of network topology, types of data services, and number of cluster nodes on network performance under the proposed protocol were analyzed. The protocol was compared with the clustering system. The results reveal that it achieves improved throughput, packet loss rate, delay, and channel utilization performance. • Functional experiments were performed in two network scenarios. The operational status of the eCOCM protocol was analyzed in detail based on the output and input signal waveforms of the UV nodes, and the experimental results fully confirm the validity of the protocol. [ABSTRACT FROM AUTHOR]

Serverless computing is a new concept as cloud computing, which dynamically manages the networks and is applied in Serverless Wireless Sensor Networks (SWSN) to help the networks. These networks are becoming famous for monitoring various physical and environmental factors. Serverless computing also facilitates the networks by offering an extensive range of applications. Different applications have been designed for monitoring purposes where the sensor nodes sense the data and transmit it to the base station through single or multi-hop routing. However, existing routing protocols cannot manage the sensor nodes' energy issues because of the complex routing processes and depleted their power before their time. Because of these limitations, the nodes close to BS continuously rely on the network for data forwarding. As a result, these nodes cause energy consumption and lead to a useless state. This paper proposes a serverless architecture and designs an Enhanced Centroid-based Energy Efficient Clustering (ECEEC) protocol for SWSN networks. The proposed serverless architecture provides automated scalability, cost-effective services, and stateless execution. In addition, the proposed protocol offers the cluster head selection and its rotation to maximize the energy efficiency in the network. Furthermore, gateway nodes are chosen in every cluster to overcome the load on the cluster head. Simulation results indicated the excellent performance of the proposed protocol as compared to the existing routing protocols concerning network lifetime and energy consumption. The proposed protocol shows better reliability with nodes failing at 650 rounds compared to 600 rounds, especially with 5 % and 10 % Cluster Heads. The proposed protocol exhibits superior energy efficiency consumption of SNs under varying CH percentages, indicating the protocol's consistent performance across different scenarios. [ABSTRACT FROM AUTHOR]

Quantum network coding can effectively alleviate bottlenecks in quantum networks thus improving the transmission efficiency and the throughput of the quantum network. Although various quantum network coding protocols have been constructed, most of them focus mainly on addressing the communication congestion issue of simultaneously transmitting single-qubit states via the bottleneck channel in quantum networks. In this paper, a protocol for the quantum two-pair unicast transmission of multi-particle states using quantum time-bin multiplexing is proposed. Parallel entanglement is established in a heralded way between two-dimensional quantum memories (QMs) of intermediate nodes by transmitting a high-dimensional encoded single photon via the bottleneck channel. Then the quantum unicast transmission of multi-particle states can be achieved by using quantum teleportation and the resultant entangled pairs. Additionally, a security enhanced protocol is presented when dishonest intermediate nodes or outside eavesdroppers are taken into account. No alternative measurements are needed to check security. This makes the present protocol cost-effective and efficient. Compared with existing methods, no pre-shared entangled states are required. This provides a new perspective for the development of quantum networks. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed protocol for tracking the global maximum supremum (or minimum infimum) of a set of exogenous time-varying signals. Specifically, each agent has only access to one of these signals and, by implementing the proposed protocol, it is able to track in finite-time the maximum supremum (or the minimum infimum) of the exogenous time-varying signals in a distributed fashion. No assumption is made on the network size and, remarkably, the communication graph is directed (possibly switching) with the only requirement to be strongly connected at all times. The behavior of the protocol with open networks is discussed and numerical simulations are provided to corroborate the theoretical findings. [ABSTRACT FROM AUTHOR]

Pre-trained models such as BERT have made great achievements in natural language processing tasks in recent years. In this paper, we investigate the privacy-preserving pre-training based neural network inference in a two-server framework based on additive secret sharing technique. Our protocol allows a resource-restrained client to request two powerful servers to cooperatively process the natural processing tasks without revealing any useful information about its data. We first design a series of secure sub-protocols for non-linear functions used in BERT model. These sub-protocols are expected to have broad applications and of independent interest. Based on the building sub-protocols, we propose SecBERT, a privacy-preserving pre-training based neural network inference protocol. SecBERT is the first cryptographically secure privacy-preserving pre-training based neural network inference protocol. We show security, efficiency and accuracy of SecBERT protocol through comprehensive theoretical analysis and experiments. [ABSTRACT FROM AUTHOR]

Filtered Smith predictors are well established for controlling linear plants with constant time delays. Apart from this classical application scenario, they are also employed within networked control loops, where the measurements are sent in separate packets over transmission channels that are subject to time-varying delays. Consequently, classical tools for the stability analysis, e.g., for time delay systems, have to be extended to facilitate an explicit consideration of network-induced effects such as packet skipping and disordering of sent packets. The present paper illustrates that the time-varying delays and, particularly important, the packetized character of the transmissions have to be explicitly taken into account for the stability analysis. Three network protocols, which use different packet selection and hold mechanisms, are considered to state criteria for the robust stability of the networked feedback loops with filtered Smith predictors. They are based on the small gain theorem and allow a computationally inexpensive way to check stability for the case with uncertain plant models and bounded time-varying packet delays in the communication channels. • Filtered Smith predictor for packet-based networked systems. • Communication network with bounded and time-varying packet delays. • Three different network protocols (different packet skipping and hold mechanisms). • Easy-to-use stability analysis for uncertain plants and time-varying packet delays. [ABSTRACT FROM AUTHOR]

• A dynamic-distributed structure is designed as a satellite organizational structure. • An improved contract network protocol under the dynamic-distributed structure is proposed. • A blackboard model mechanism is proposed to coordinate the satellites under uncertainty. • An online single-satellite scheduling algorithm is designed. • The applicability of the proposed methods to different implementations of problems is studied. To meet the demand for real-time response to emergent events in the uncertain environment, the multi-autonomous-satellite system with real-time inter-satellite links and on-board scheduling capability has been proposed. This paper focuses on the multi-autonomous-satellite coordination and scheduling problem which is formulated by a novel mathematical model based on the multi-agent system (MAS). To solve the problem, we firstly analyze general organizational structures for the MAS and propose a new dynamic-distributed organizational structure. For these different structures, an improved contract network protocol (ICNP) and a blackboard model (BM) negotiation mechanism are proposed to coordinate the satellites. Then, an online single-satellite scheduling algorithm is proposed to schedule the tasks. In the experiments, we build up a multi-satellite system to analyze the performance of different autonomous coordination mechanisms. Experimental results indicate that the ICNP mechanism can increase the total revenue and reduce the inter-satellite communication cost. In scenarios where satellites could break down randomly, the BM can reduce the revenue losses and the number of task failures efficiently, which proves the good performance of the proposed methods in terms of robustness. The proposed methods have important practicality in the real application of the multi-autonomous-satellite system. [ABSTRACT FROM AUTHOR]

To evaluate pneumatic vitreolysis (PVL) in eyes with vitreomacular traction (VMT) with and without full-thickness macular hole (FTMH). Two multicenter (28 sites) studies: a randomized clinical trial comparing PVL with observation (sham injection) for VMT without FTMH (Protocol AG) and a single-arm study assessing PVL for FTMH (Protocol AH). Participants were adults with central VMT (vitreomacular adhesion was ≤3000 μm). In Protocol AG, visual acuity (VA) was 20/32 to 20/400. In Protocol AH, eyes had a FTMH (≤250 μm at the narrowest point) and VA of 20/25 to 20/400. Pneumatic vitreolysis using perfluoropropane (C 3 F 8) gas. Central VMT release at 24 weeks (Protocol AG) and FTMH closure at 8 weeks (Protocol AH). From October 2018 through February 2020, 46 participants were enrolled in Protocol AG, and 35 were enrolled in Protocol AH. Higher than expected rates of retinal detachment and tear resulted in early termination of both protocols. Combining studies, 7 of 59 eyes (12% [95% CI, 6%–23%]; 2 eyes in Protocol AG, 5 eyes in Protocol AH) that received PVL developed rhegmatogenous retinal detachment (n = 6) or retinal tear (n = 1). At 24 weeks in Protocol AG, 18 of 23 eyes in the PVL group (78%) versus 2 of 22 eyes in the sham group (9%) achieved central VMT release without rescue vitrectomy (adjusted risk difference, 66% [95% CI, 44%–88%]; P < 0.001). The mean change in VA from baseline at 24 weeks was 6.7 letters in the PVL group and 6.1 letters in the sham group (adjusted difference, –0.8 [95% CI, –6.1 to 4.5]; P = 0.77). In Protocol AH, 10 of 35 eyes (29% [95% CI, 16%–45%]) achieved FTMH closure without rescue vitrectomy at 8 weeks. The mean change in VA from baseline at 8 weeks was –1.5 letters (95% CI, –10.3 to 7.3 letters). In most eyes with VMT, PVL induced hyaloid release. In eyes with FTMH, PVL resulted in hole closure in approximately one third of eyes. These studies were terminated early because of safety concerns related to retinal detachments and retinal tears. [ABSTRACT FROM AUTHOR]

This paper examines the H ∞ performance problem of the edge agreement protocol for networks of agents operating on independent time scales, connected by weighted edges, and corrupted by exogenous disturbances. H ∞ -norm expressions and bounds are computed that are then used to derive new insights on network performance in terms of the effect of time scales and edge weights on disturbance rejection. We use our bounds to formulate a convex optimization problem for time scale and edge weight selection. Numerical examples are given to illustrate the applicability of the derived H ∞ -norm bound expressions, and the optimization paradigm is illustrated via a formation control example involving non-homogeneous agents. [ABSTRACT FROM AUTHOR]

The future network is expected to support extremely large bandwidth, ultra-low latency or deterministic delay, extremely high reliability, and massive connectivity for novel forward-looking scenarios. As one of the most fundamental parts of the network, routing plays a vital role in a well-performed network. Recently, some new techniques using machine intelligence to optimize the network routing have been proposed. Although they have demonstrated great potential to improve the network performance, it is still a great challenge to apply machine intelligence-based routing in real network environment due to the limitations of current network architectures and protocols. Fortunately, the future network research program is on-going for designing new network paradigms, which provides an opportunity to address those limitations. In this paper, we investigate state-of-the-art techniques in machine intelligence-enabled network routing and discuss the development trends of machine intelligence-enabled routing optimization techniques for the future network. [ABSTRACT FROM AUTHOR]

This article connects mobile terminals through improved network protocols, and connects monitoring devices through improved network protocols in the local area network. At the same time, it can convert mobile terminal requests into requests that comply with improved network protocols and forward them to monitoring devices. Method of three-dimensional feature extraction based on dynamic data. First, normalize the coordinates and scales of the three-dimensional calculus model, and use two kinds of data (voxel representation and pixel representation) to deal with video object recognition. Then construct a convolutional neural network as an input to the network, extract visual information and geometric information, and use deep learning to improve the recognition ability of single-modal features. Based on the convolutional neural network, the geometric descriptor and the view descriptor of the three-dimensional calculus model are extracted separately, and the two feature descriptors are fused in a network to find the association between the patterns. After forming the fused feature descriptor, it is applied to micro Classification and retrieval of integral 3D features. The multi-feature fusion layer can not only learn more distinguishing features of the two descriptors, but also supplement relevant information between the two descriptors. Compared with using these two representations alone, this method produces a much better classifier and improves retrieval efficiency. [ABSTRACT FROM AUTHOR]

• The Network Canvas suite consists of three applications: Architect ; Interviewer ; Server. • These applications simplify the collection of complex social network data. • Our work prioritizes flexibility, intuitive design, integrated workflow, and collaboration. Self-reported social network analysis studies are often complex and burdensome, both during the interview process itself, and when conducting data management following the interview. Through funding obtained from the National Institute on Drug Abuse (NIDA/NIH), our team developed the Network Canvas suite of software – a set of complementary tools that are designed to simplify the collection and storage of complex social network data, with an emphasis on usability and accessibility across platforms and devices, and guided by the practical needs of researchers. The suite consists of three applications: Architect: an application for researchers to design and export interview protocols; Interviewer: a touch-optimized application for loading and administering interview protocols to study participants; and Server: an application for researchers to manage the interview deployment process and export their data for analysis. Together, they enable researchers with minimal technological expertise to access a complete research workflow, by building their own network interview protocols, deploying these protocols widely within a variety of contexts, and immediately attaining the resulting data from a secure central location. In this paper, we outline the critical decisions taken in developing this suite of tools for the network research community. We also describe the work which guides our decision-making, including prior experiences and key discovery events. We focus on key design choices, taken for theoretical, philosophical, and pragmatic reasons, and outline their strengths and limitations. [ABSTRACT FROM AUTHOR]

The purpose of this research is to investigate the use of a communication network utilizing Long Range (LoRa) low-power wide-area network protocol for the telemetry of detected target chemicals. The sensor platform under development allows traditional electrochemical techniques to be executed with a low Size, Weight, and Power (low SWaP) system that is deployable using an autonomous or remote-controlled vehicle. Once in the field, the sensors communicate target chemical concentrations to a centralized gateway through LoRa to an Internet of Things (IoT) network. Researchers are currently deploying the prototype network for field testing of each node's sensing, meshing, and communication capabilities throughout all weather climates. Developing a robust and dynamic sensor network to monitor the environment and provide a live data feed to detect chemicals of interest in the environment eliminates the need for direct human interaction. The low power consumption of LoRa allows the network nodes to be deployed for an extended amount of time on a single battery supply. [ABSTRACT FROM AUTHOR]

Geocast routing aims the transmission of a message to a community of vehicles in the same geographical area. The GPS information of vehicles, especially taxis, in a city gives reliable information about the traffic pattern of a city. With the help of this information smart models can be created to use when making routing decisions. In this paper, a smart geocasting protocol, GeoAKOM, is introduced and implemented by using the GPS data of taxis in Bursa city, Turkey. In GeoAKOM, the mobility pattern of city is analized in two levels as in GeoMobCon introduced earlier. In the macroscopic level analysis, the city is segmented into clusters using k-means clustering and optimal paths for a message is generated using these clusters. In the microscopic level, mobility based likelihood value is used to make routing decision. The message is transmitted if the encountered vehicle has a larger mobility based likelihood or contact history based likelihood value than the carrying vehicle as in GeoMobCon. Moreover, in GeoAKOM, the next cluster of a vehicle is predicted with the help of all k-order Markov model (AKOM) by using GPS records of all vehicles. Mobility based likelihood calculations are performed by using this prediction. With these features, GeoAKOM provides a robust solution for the vehicles which do not have large GPS record history and which are relatively new in the system. Simulations on real world taxi GPS data are compared for various number of clusters in terms of delivery ratio, average delay, and hop count by using the ONE simulator. Simulation results show that, GeoAKOM provides promising results when compared with GeoMobCon and the First Contact routing algorithms. [ABSTRACT FROM AUTHOR]

Industrial Internet-of-Things systems suffer from a vast and vulnerable attack surface, raising widespread concerns about shielding IIoT devices from malicious attacks and reducing cyber risks. Device identification is the prerequisite to safeguard IIoT systems. We leverage the observation that IIoT network protocol implementations vary due to different hardware architectures/configurations and design tasks of IIoT devices, which cause the difference in their network traffic payloads. Specifically, we develop a novel neural network to learn the semantic/syntax features among multiple IIoT packets. The neural network has multiple branches, each of which consists of convolution layers, attention modules, and highway units for learning the classification model of IIoT devices. To validate the precision and recall of our neural network in IIoT devices fingerprinting, we have implemented a prototype of the proposed IIoT device identification system. Our results show that our approach achieves 95.8% precision and 95.4% recall, significantly outperforming other classification models. • We propose a novel IIoT fingerprinting approach based on neural network. • We conduct experiments to validate the effectiveness of it. • The results show that our approach can achieve 95.8% precision. • We demonstrate the usefulness of fingerprinting in application. • Our approach is useful in shielding industrial systems. [ABSTRACT FROM AUTHOR]

Time cost is an important indicator for evaluating the control protocol of the designed network system. The issue of flocking in Cucker–Smale type models is investigated in this article. Two new switching protocols are articulated to achieve finite-time (FT) and fixed-time (FDT) flocking. Sufficient conditions and the upper bounds of time cost (TC) for flocking are obtained. The influence of parameters and group size on TC is revealed. Especially, the new control strategy proposed successfully reduces the convergence time compared to the general FT and FDT control protocols. • The new switching protocols can ensure the Cucker–Smale type models achieve finite-time and fixed-time flocking. • The upper bound estimation of flocking time cost convincingly illustrates that the models achieve flocking faster. • It is revealed that the time cost is closely related to both the control parameters and the group size. [ABSTRACT FROM AUTHOR]

In this paper, the output feedback H ∞ control is investigated for the networked singularly perturbed systems (SPSs) with Markov lossy network, in which the packet loss probability varies in different modes. A new network mode-dependent round-robin-like protocol (RRLP) is introduced to the networked SPSs, which can dynamically adjust the number of the selected sensor nodes according to the network environment condition. Based on this RRLP and Markov lossy network, a Markov mode and scheduling order co-dependent output feedback controller is constructed to ensure the system control performance. By constructing a novel Lyapunov-Krasovskii functional dependent on the singular perturbation parameter, Markov mode, and scheduling order simultaneously, sufficient conditions of mean square stability for SPSs are obtained, and numerical stiffness is avoided. Finally, a direct current motor-controlled inverted pendulum example is proposed to verify the effectiveness of our main results. • Compared with the conventional RRP, a network mode-dependent RRLP is first introduced into SPSs, by which the number of scheduled sensors can be adjusted appropriately according to different network environments. • Based on the Markov lossy network and multi-node RRP, a novel output feedback controller is designed, which can effectively improve the control performance of system. • By constructing a new Lyapunov-Krasovskii functional dependent on SPP, Markov mode, and scheduling order simultaneously, the sufficient condition of the mean square stability is obtained for SPSs. [ABSTRACT FROM AUTHOR]

In view of the security threats posed inside and outside the network due to the weaknesses of network protocols and systems, power line and wireless converged communications have security problems in communication connections that appear in environments where heterogeneous networks overlap. In order to cope with the problems of network delay and data transmission security in smart grid, this paper proposes an online monitoring security protection method based on edge nodes, which manages user trust under the premise of not leaking grid user data, and establishes a personalized machine learning model. This method not only guarantees users a secure communication experience, but also ensures users' real-time network connection and content acquisition, and can obtain a fast and personalized user experience. [ABSTRACT FROM AUTHOR]

Massively dense deployment of Internet of Things (IoT) devices has put a stringent requirement on cellular networks to provide convenient service for not only human type traffic (HTC) but also for bursty traffic for IoT devices. Any bottleneck in the random access process means the bottleneck of the entire system because it is the first step before scheduled access. Access class barring (ACB) scheme is one of the key schemes in long term evolution advanced (LTE-A) to control the congestion in a random access process in which the access of some devices is barred based on a parameter, ACB factor, to relieve the congestion. In this paper, we analyze the ACB factor and criteria of its selection as the optimal selection of the ACB factor is essential for the maximum throughput of the system. The metrics used in the analysis of the ACB factor are total service time (TST), access delay and maximum collision, success, and idle probabilities with fixed and optimal ACB factor. Simulation results in MATLAB provide the complete picture of the behavior of the ACB factor and its control, used in the random access process. [ABSTRACT FROM AUTHOR]

We consider networks where each node represents a server with a queue. An active node deactivates at unit rate. An inactive node activates at a rate that depends on its queue length, provided none of its neighbors is active. For complete bipartite networks, in the limit as the queues become large, we compute the average transition time between the two states where one half of the network is active and the other half is inactive. We show that the law of the transition time divided by its mean exhibits a trichotomy, depending on the activation rate functions. [ABSTRACT FROM AUTHOR]

In this paper, the distributed set-membership filtering problem is investigated for general nonlinear systems subject to Round-Robin and stochastic communication protocols over sensor networks. The considered disturbances are assumed to be unknown but bounded within certain known ellipsoidal regions. Two types of frequently used protocols, i.e., the Round-Robin and stochastic communication protocols are adopted separately to regulate the data transmission among sensor nodes. According to the Round-Robin protocol, each node is able to receive information from only one of its neighboring nodes in a circular order at each time step, whereas the stochastic communication protocol allows each node randomly receive the information sent from one of the neighboring nodes. By resorting to the recursive linear matrix inequalities approach, sufficient conditions are established for the existence of the desired distributed filter, guaranteeing that the state estimates are constrained within certain pre-determined ellipsoidal regions at each time step. Then two optimization problems aiming to minimize the ellipsoids (in the sense of matrix trace) are put forward to seek the locally optimal filtering performance. Finally, simulation examples are given to illustrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

IEEE 802.15.4 protocol is intended to accomplish the characteristics of low power and low rate Wireless Sensor Network. It employs carrier sense multiple access with collision avoidance (CSMA/CA) protocol to access the network using either unslotted or slotted mode. This paper concentrates on the unslotted CSMA/CA where the node tends to wait for a very limited backoff exponent value, and cannot perform clear channel assessment until backoff procedure is completed. Therefore, the collision probability and the average delay are high. To enhance the unslotted CSMA/CA performance, this paper proposes a modified unslotted CSMA/CA that divides the backoff delay into Main Backoff and Secondary Backoff. The Markov model for the modified CSMA/CA is presented to assess a single hop IEEE 802.15.4 behavior, and derive expressions for average delay, energy consumption and reliability. An optimization problem is also presented to minimize the delay while guaranteeing energy consumption and reliability constraints for the modified CSMA/CA. OPNET simulation tool is applied to compare the modified to the standard unslotted CSMA, and to validate the Markov model proposed. The results demonstrate that the modified CSMA improves the reliability, while reducing the average delay significantly. [ABSTRACT FROM AUTHOR]

As the use of Wireless Sensor Networks grows, many challenging issues with these networks arise. The utilization of power consumption is one of the most significant issue due to the limited energy constraints of the individual sensor nodes. This limitation imposes a challenge to design the best energy-efficient routing mechanism. This work presented an Energy-Efficient Gossiping protocol (EEGossip) that routes data to the sink by choosing the optimal next node. EEGossip uses Chebyshev distance, residual energy and the sink distance as factors when determining the optimal next node. The result of the proposed work has shown that the proposed protocol improves the total energy consumption of the network and leverages the network lifetime since it decreases the computational overhead and ensures that the best next node is chosen. [ABSTRACT FROM AUTHOR]

Wireless sensor networks is made up of many tiny nodes that has the ability to measure physical phenomena and send the collected measurements to the sink node using multiple-hop protocol with short range transmission. One of the main factors that can be considered to increase the sensor network life is routing protocol. The main goal of routing protocol is to select the most optimal path and make decision of sending the gathering data to the sink node. Inefficient routing protocol leads to more re-transmission of data which consume more energy.Thus, a careful and comprehensive performance analysis of the routing protocols used in any wireless sensor network is required. The main goal of this paper is to study the performance of the RPL protocol under three different MAC protocols named; ContikiMac, CXMAC, NullRDC in terms of end-to-end delay, packet delivery ratio and power consumption to find the best behaviour of the RPL routing protocol under the MAC protocols effect. The results show that NullRDC is better in terms of latency while the ContikiMac outperforms the others in terms of power consumption. [ABSTRACT FROM AUTHOR]

Contrary to many previous studies on population protocols using the uniformly random scheduler, we consider a more general non-uniform case. Here, pair-wise interactions between agents (moving and communicating devices) are assumed to be drawn non-uniformly at random. While such a scheduler is known to be relevant for modeling many practical networks, it is also known to make the formal analysis more difficult. This study concerns data collection , a fundamental problem in mobile sensor networks (one of the target networks of population protocols). In this problem, pieces of information given to the agents (e.g., sensor readings) should be eventually delivered to a predefined sink node without loss or duplication. Following an idea of the known deterministic protocol TTF solving this problem, we propose an adapted version of it and perform a complete formal analysis of execution times in expectation and with high probability (w.h.p.). We further investigate the important issue of energy consumption. The goal is to improve TTF in terms of energy complexity, while still keeping good time complexities (in expectation and w.h.p.). Namely, we propose a new parameterized protocol for data collection, called lazy TTF, and present a study showing that an appropriate choice of the protocol parameters can considerably improve energy performances (compared to TTF), at a slight expense of time performance. [ABSTRACT FROM AUTHOR]

This paper concentrates on the design of an event-triggered communication strategy for secondary multi-agent systems. Many existing results in this field usually require centralized information depending on the Laplacian matrices. In a real application, however, such the constraint is conservative. To address it, this paper proposes an event-triggered sampling mechanism for interagent communication with updated thresholds. Accordingly, consensus protocols with adaptive coupling control gains are proposed for both a fixed topology and switching topologies. It is proven that the proposed method guarantees the leader-following consensus for second-order multiagent systems with an arbitrarily connected topology and even with jointly connected switching topologies. The effectiveness of the proposed scheme is verified by simulation examples. • An adaptive event-triggered strategy makes MASs independent of spectrums of Laplacian matrices. • A fully distributed protocol for nonlinear MASs eases the burden of communication channels. • The networking protocol can be easily generalized to jointly connected switching topologies. [ABSTRACT FROM AUTHOR]

• The performance of SCLEACH, SCPEGASIS, SCTEEN is analyzed. • Single report is enough to transfer to the sink, to avoid redundant reports. • Proposed protocols have been compared with k-d tree algorithm. • Five parameters are considered for the analysis. SCHRP model takes less time to measure the parameters of the network. In Wireless Sensor Networks (WSNs), the most significant task is to gather the data from the sensor nodes available in specific region available in event sensing field. The nodes in WSNs are energy constrained. To enhance the lifetime of WSNs, energy efficient protocols are needed. Spatial Correlation based Low Energy Adaptive Clustering Hierarchy (SCLEACH), Spatial Correlation based Power-efficient Gathering in Sensor Information Systems (SCPEGASIS), Spatial Correlation based Threshold Sensitive Energy Efficient Sensor Network Protocol (SCTEEN) are well-designed solutions to rectify this problem. These protocols minimize the overall dissipation by means of individual sensor nodes located in the network. Spatial correlation based Hierarchical Routing Protocols (SCHRP) adapt clustering concept and enhance the energy efficiency and the performance of over all network. The Performance of SCHRP model is compared with existing LEACH and PEGASIS, TEEN protocols and results have been taken for various parameters such as End-to-End delay, Packet drop, Packet delivery ratio, Throughput, Energy Efficiency and Energy Consumption. The proposed SCLEACH has 6.35% higher energy efficiency than the existing LEACH protocol. The impact of the proposed protocols are evaluated using various parameters and compared with k-d tree algorithm. The importance of spatial correlation based routing concept is analyzed with respect to k-d tree algorithm and the simulation results have been taken using Network Simulator tool. [ABSTRACT FROM AUTHOR]